Buried by time, dust and BeEF

For those who do not listen Mayhem and black metal, the talk title
might seem a bit weird, and I can't blame you.
You know the boundaries of the Same Origin Policy, you know SQL
injection and time-delays,
you know BeEF. You also know that when sending cross-domain XHRs you
can still monitor the timing of the response: you might want to infer
on 0 or 1 bits depending if the response was delayed or not.
This means it's possible to exploit every kind of SQL injection,
blind or not blind, through an hooked browser, if you can inject a
time-delay
and monitor the response timing.
You don't need a 0day or a particular SOP bypass to do this,
and it works in every browser.
The potential of being faster than a normal single-host multi-threaded SQLi
dumper will be explored. Two experiments will be shown: WebWorkers as well
as multiple synched hooked browsers, which split the workload
communicating
partial results to a central server.
A pure JavaScript approach will be exclusively presented during this talk,
including live demos. Such approach would work for both internet facing
targets as well as
applications available in the intranet of the hooked browser.
The talk will finish discussing the implications of such an approach
in terms of Incident Response and Forensics,
showing evidence of a very small footprint.

6.
The issue
§ If the problem is getting caught:
– Spawn from 3 to X VPSs:
1. Each of them has SQLmap
2. Each of them dump a different data set
3. Each of them uses a different chain of proxies
4. When 1 data set is dumped, change the proxy chain.
§ Restart from point 1
§ Downside: might not be cost-effective (depends
on the data dumped :-). I don’t have enough
money…

8.
The issue
§ Solving the issue without paying for multiple
VPSs/infrastructure….

9.
Use BeEF
§ Exploit Time-Based Blind SQLi from multiple
hooked browsers
§ It’s the hooked browser that (just through
JavaScript) send requests and dump data
§ A forensic team will see a connection from
multiple hooked browsers at the same time

10.
Use BeEF
§
§
§
§
§
Install BeEF and OpenVPN on a VPS
VPN client -> TOR (or other proxies) -> VPS
Hook some browsers
Instruct the browsers to dump data for you
When finished, terminate the VPS

11.
Some background
§ Same-Origin Policy and XHR
§ Why Time-based Blind SQLi?
§ The beautiful features of MSSQL
§ BeEF and putting all together

13.
Same-Origin Policy and XHR
§ Cross-origin XmlHttpRequest
– You can’t read the HTTP Response (you need
Access-Control-Allow-Origin, or a SOP bypass)
But….
– You can still send the request
§ The request arrives to the destination
– You can check the state of the request
§ xhr.readyState

15.
Same-Origin Policy and XHR: implications
§ If you can know if xhr.readyState == 4
– You can monitor the timing
– Just create 2 Date objects before and after sending
the request, and do simple math :D

19.
Why Time-based Blind SQLi?
§ If we can infer the timing of the response, we
can exploit Time-based blind SQLi cross-origin!
§ Actually any type of SQL injection flaw can be
exploited with Time-based blind vectors
§ Sometimes time-based blind is the only way to
exploit an instance of SQLi
§ Sometimes SQLmap (great tool, kudos Bernardo!) is able to
exploit SQL injections only using time-based vectors

20.
The beautiful features of MSSQL
§ http://msdn.microsoft.com/en-us/library/
ms187331.aspx

22.
The beautiful features of MSSQL
§ MySQL and Postgres do not support this
– Postgres example: http://www.postgresql.org/docs/
8.2/static/functions-datetime.html
§ Still, you could use BENCHMARK or other
similar functions
– Excessive CPU load if parallelized? Probably

23.
The beautiful features of MSSQL
§ With DBs != MSSQL you can still exploit SQLi
using Time-based Blind vectors from the
browser
– But you can’t parallelize requests
§ Most ASP/.NET applications uses MSSQL
§ MSSQL presence in the internet is widespread

25.
BeEF and putting all together
§ MSSQL only right now
– PoC retrieving DB and Table names
§ Concurrent approach
– Multiple WebWorkers
– Multiple hooked browsers
§ 3 to 4 times faster than SQLmap
§ They disabled multi-threading when using time-based blind
vectors, with every database, even MSSQL
§ Can be re-enabled hacking the source code

28.
Concurrent approach: WebWorkers
§ Given a pool of WebWorkers (controlled by a
state-machine in JavaScript)
§ Every WW manage one byte (7 requests each)
§ You can retrieve up to <pool_size> bytes at the same
time
§ WW communicate with the “parent” state-machine
with postMessage()
§ Everything is happening from and in the browser

29.
Concurrent approach: multiple browsers
§ As we can parallelize requests with
WebWorkers, we could even distribute the data
dumping process across multiple browser
– Reliability
§ Minimize the impact of loosing an hooked browser
– Stealthiness (and piss-off forensic guys)
§ The attack looks like coming from different sources
– Fun (and piss-off forensic guys)
§ You want to target company X, which has company Y as
competitor: hook some company Y browsers, and instrument
them to exploit a SQLi in company X website :D
§ Company X will think company Y is attacking them

30.
BeEF and putting all together
§ Demo
– Video, as last year here in RuxCon the live demo
failed (Vmware Fusion issues, broken VM, porco dio!)
– https://vimeo.com/78055061

31.
BeEF and putting all together
§ If you liked this talk, support BeEF buying:
§ Pre-order on Amazon available, out March 2014
§ 50% of revenues will be used for the BeEF
project (testing infrastructure, etc..)